Bayesian updating during development predicts genotypic differences in plasticity : PREDICTING GENOTYPIC DIFFERENCES IN PLASTICITY

Psychologists and economists have long appreciated the contribution of reward history and expectation to decision-making. Yet we know little about how specific histories of choice and reward lead to an internal representation of the "value" of possible actions. We approached this problem through an integrated application of behavioral, computational, and physiological techniques. Monkeys were placed in a dynamic foraging environment in which they had to track the changing values of alternative choices through time. In this context, the monkeys' foraging behavior provided a window into their subjective valuation. We found that a simple model based on reward history can duplicate this behavior and that neurons in the parietal cortex represent the relative value of competing actions predicted by this model.

When the optimal phenotype differs among environments, adaptive phenotypic plasticity can evolve unless constraints impede such evolution. Costs and limits of plasticity have been proposed as important constraints on the evolution of plasticity, yet confusion exists over their distinction. We attempt to clarify these concepts by reviewing their categorization and measurement, highlighting how costs and limits are defined in different currencies (and may describe the same phenomenon). Conclusions from studies that measure the costs of plasticity have been equivocal, but we caution that these conclusions may be premature owing to a potentially common correlation between environment-specific trait values and the magnitude of trait plasticities (i.e. multi-collinearity) that results in imprecise and/or biased estimates of the costs. Meanwhile, our understanding of the limits of plasticity, and how they may be underlain by the costs of plasticity, is still in its infancy. Based on our re-evaluation of these constraints, we discuss areas for future research.

Cryptic genetic variation (CGV) is invisible under normal conditions, but it can fuel evolution when circumstances change. In theory, CGV can represent a massive cache of adaptive potential or a pool of deleterious alleles that are in need of constant suppression. CGV emerges from both neutral and selective processes, and it may inform about how human populations respond to change. CGV facilitates adaptation in experimental settings, but does it have an important role in the real world? Here, we review the empirical support for widespread CGV in natural populations, including its potential role in emerging human diseases and the growing evidence of its contribution to evolution.